Better cost and outcome analysis for new medical devices
Health systems need to constantly adapt to an ever-changing environment. These changes are reflected in the very nature of threats to public health, and also in advances in research that keep bringing existing practices into question. Policymakers need to keep adapting to these trends and – when it comes to novel medical devices – cost and outcome analysis is crucial to making the right call. This process is at the heart of Health Technology Assessment (HTA): HTA bodies are asked to evaluate how a new technology compares to existing alternatives. They do so by assessing the device’s impact on health and well-being, possible side effects, costs implications for the patient and impact on the organisation of healthcare systems. Enter the EU-funded COMED (Pushing the boundaries of Cost and Outcome analysis of Medical Technologies) project, which aimed to refine existing methods of cost and outcome analysis for medical devices. “Whilst data on costs and health outcomes are available from an increasing range of sources, there are still numerous methodological issues that must be explored,” says Aleksandra Torbica, director of the University of Bocconi’s Centre for Research on Health and Social Care Management (CERGAS) and coordinator of COMED. One such issue is the use of real-world data (RWD) in cost and outcome analysis. This data, which includes the likes of databases, surveys, patient chart reviews, clinical trials, patient registries and observational data from cohort studies, can support decision-making before and after market entry. COMED aimed to provide empirical evidence on this contribution. “We systematically mapped existing RWD sources in Europe for three selected case studies: hip and knee arthroplasty, percutaneous transcatheter valve replacement technology, and procedures performed by the da Vinci Surgical System. From then on, we provided a comprehensive assessment of their content and evaluated their appropriateness for conducting HTAs of medical devices,” Torbica explains. In total, the consortium identified 71 RWD sources in arthroplasties, 95 in valve replacement and 71 in robotic procedures. After an in-depth analysis, they concluded that, while RWD sources indeed bear great potential for an HTA of medical devices, remaining challenges include data accessibility, lack of standardisation of health and economic outcomes, and inadequate comparators.
Surrogate endpoints
A second issue identified by COMED is the use of surrogate endpoints – effects of a specific treatment that may correlate with a real clinical endpoint but do not necessarily have a guaranteed relationship – to support the licensing and commercialisation decisions of medical devices. “The use of surrogate endpoints is becoming increasingly important for faster patient access to innovative health technologies. We screened available guidelines from HTA bodies and demonstrated an increase in their use over the past decade. But there are considerable differences in the depth of this guidance across agencies,” Torbica notes. The project team concludes that further methodological and policy research on the harmonisation of approaches to surrogate outcome evidence in healthcare decision-making is warranted. Another aspect considered by COMED is coverage with evidence development (CED). These schemes consist in conditioning health insurance coverage on data gathering through a clinical trial or registry. COMED looked for challenges faced by taxpayers and manufacturers when applying CED schemes for medical devices, and found important ones at the initiation, design, implementation and evaluation stages. The project also provides recommendations and alternative strategies for future policy choices. With all these contributions, COMED is likely to contribute to improving the decision-making process in European healthcare systems. The project advances scientific knowledge, and also provides immediately applicable policy advice and tools.
Keywords
COMED, medical devices, HTA, health technology assessment, real-world data, surrogate endpoints
